Multi-Robot Task Allocation Strategies Using Auction-Like Mechanisms

Task allocation is a complex and open problem for multi-robot systems. In this paper, we present three strategies for dynamically allocating tasks in a colony of mobile robots. The system is partially inspired on auction and thresholds-based methods and tries to determine the optimum number of robots that are needed to solve specific tasks, or sub-goals, in order to minimize the execution time of a mission. The method has been extensively tested for a modification of the well-known foraging task. Initial situations with different combinations of workload and work capacity have been used to test the proposed solution on robot teams with different homogeneities. Experimental results are presented to show the benefits of the proposed methods.